Vector-borne diseases are one of the most prevalent types of emerging infectious diseases worldwide and are a major threat to public health. Our collaborative team has used our extraordinary set of samples - which were collected during the time and space of a rapid range expansion of Ixodes scapularis ticks - to elucidate the environmental and climatic factors that facilitated the emergence of this disease vector in the Northeastern United States. The proposed research aims are to identify the patterns of, and processes affecting, the population dynamics of three important emerging human pathogens - Borrelia burgdorferi, Anaplasma phagocytophilum, and Babesia microti -by analyzing genome sequences in coalescent-based, phylodynamic analytical frameworks. The biological, environmental, and technical knowledge we have acquired, along with our ever-expanding sample set (75,887 tick samples from 515 sites over 14 years), provides a powerful system to identify environmental factors affecting the demography of these pathogens. We propose to use this dataset to (a) determine the current and historical dynamic patterns of 3 tick-borne pathogens; (b) identify and quantify the influence of environmental features on the demography of each microbial species; and (c) use prospective sampling to validate demographic models and the influence of environmental factors on migration and population growth. Characterizing the environmental factors that affect the demography of emerging pathogens at very fine scales is achievable through the application of sophisticated analyses to populations of genomes. To this end, we developed the selective whole genome amplification (SWGA) technique to generate sufficient quantities of microbial genomic DNA for next generation sequencing. Using this enabling technology, we can sequence hundreds of microbial genomes in order to develop mechanistic models describing how environmental factors impact migration and population growth; few examples are known of the functional bases determining the rates and directions of dispersal of pathogens in nature. The proposed phylogeographic diffusion modeling framework is ideally suited to assess how each species is geographically structured and to identify the environmental features associated with migration and growth. We will utilize the results of our proposed studies to develop and experimentally validate models that estimate future disease spread into novel environments. Uncovering common biotic and abiotic factors that influence the distribution and abundance of, and thus disease risk from, all of these vector-borne pathogens is immediately applicable to disease control strategies.